Integration of Facial Form and Facial Motion During Face Recognition

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The ability to integrate information provided by the form and motion of faces is a crucial task for social animals like humans. Yet, most of what is known about face perception comes from studies relying on static images of faces. Surprisingly little is known about how and when humans integrate form and motion to recognize a face. This gap is partly due to the previous lack of well-controlled dynamic face stimuli. Moreover, quantitative models linking brain activity to behavior are needed to study the integration of facial form and motion in the human brain. Recently, cue integration research has benefited from the application of so-called optimal cue integration models to investigate multisensory integration. Here, we plan to apply optimal cue integration models to investigate the mechanisms and the neural basis of facial form and motion integration during face recognition.In particular, we aim to address the following research questions: First, what are the specific weights and functions which humans apply when integrating facial motion and form during face recognition? We plan to answer these questions by combining well-controlled dynamic face stimuli, psychophysics and quantitative predictions of optimal cue integration models. Second, which cortical areas are involved in the integration of facial form and motion during face recognition? To this end, in a neuroimaging study, we want to compare behavioral performance to decoded neural activity based on optimal integration theory.The results of this project will have important implications for cognitive, computational and neural models of face perception that currently propose anatomically and functionally distinct neural pathways for the processing of facial form and motion. Moreover, the results will contribute to understanding, diagnosis and therapy of disorders involving dysfunctions of face perception found for example in prosopagnosia or autism spectrum disorders.